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  UNet is a machine learning model that produces a segmentation mask for an image. The most basic use case will label each pixel in the image as being in the foreground or the background. More advanced usage will assign a class label to each pixel. This version of the model was trained on the data from Kaggle's Carvana Image Masking Challenge (see https://www.kaggle.com/c/carvana-image-masking-challenge) and is used for vehicle segmentation.
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- This model is an implementation of Posenet-Mobilenet found [here](https://github.com/milesial/Pytorch-UNet).
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  This repository provides scripts to run Unet-Segmentation on Qualcomm® devices.
 
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  UNet is a machine learning model that produces a segmentation mask for an image. The most basic use case will label each pixel in the image as being in the foreground or the background. More advanced usage will assign a class label to each pixel. This version of the model was trained on the data from Kaggle's Carvana Image Masking Challenge (see https://www.kaggle.com/c/carvana-image-masking-challenge) and is used for vehicle segmentation.
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+ This model is an implementation of Unet-Segmentation found [here](https://github.com/milesial/Pytorch-UNet).
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  This repository provides scripts to run Unet-Segmentation on Qualcomm® devices.